R version 4.0.3 (2020-10-10) – “Bunny-Wunnies Freak Out”

Packages used for NMDS: vegan (version 2.5-7)

Methods

The document serves as an example of analyses that will be conducted to identify natural variations in benthic communities across Virginia. These NMDS will support the Genus level IBI development process. This analysis is the first run of all of reference sites in Virginia. No West Virginia DEP data is used in this analysis. Several reference sites have been sent back to Virginia DEQ biologists for one more review.

The dataset used is a subset of reference stations collected in Virginia. If stations appeared in the dataset more than 4 times, then the most recent 4 samples were used and the rest removed. Taxa that occurred in the dataset < 3% of the time were removed. The data was log10 +1 transformed. Environmental factors were compiled for each station and used to plot over the NMDS to show environmental variation associated with the community matrix. The envfit function in Vegan was used to plot the continuous environmental variables.

The first step was to read in the reference site bug taxa list and environmental factors dataset for each station. Join the environmental dataset with the bug dataset to account for multiple observations of each station and collection date and time.

Check to make sure the bug and environmental join was successful:

Number of rows in Community Matrix: 854

Number or rows in Environmental Matrix: 858

The data was log10+1 transformed. Rare taxa (<=3%) were removed.

Run NMDS for reference communities

## Run 0 stress 0.1680336 
## Run 1 stress 0.1684943 
## ... Procrustes: rmse 0.00319579  max resid 0.06499605 
## Run 2 stress 0.1682916 
## ... Procrustes: rmse 0.002731399  max resid 0.06489706 
## Run 3 stress 0.1680171 
## ... New best solution
## ... Procrustes: rmse 0.002396556  max resid 0.068746 
## Run 4 stress 0.1682642 
## ... Procrustes: rmse 0.003469849  max resid 0.06873332 
## Run 5 stress 0.1682643 
## ... Procrustes: rmse 0.003465359  max resid 0.06877089 
## Run 6 stress 0.1682404 
## ... Procrustes: rmse 0.002568496  max resid 0.06477704 
## Run 7 stress 0.1680358 
## ... Procrustes: rmse 0.002385238  max resid 0.06871529 
## Run 8 stress 0.1685203 
## Run 9 stress 0.168241 
## ... Procrustes: rmse 0.002540557  max resid 0.06483661 
## Run 10 stress 0.1691233 
## Run 11 stress 0.1680377 
## ... Procrustes: rmse 0.002381471  max resid 0.06863401 
## Run 12 stress 0.168083 
## ... Procrustes: rmse 0.00283391  max resid 0.06877781 
## Run 13 stress 0.1681116 
## ... Procrustes: rmse 0.003007188  max resid 0.06880483 
## Run 14 stress 0.1682477 
## ... Procrustes: rmse 0.003289009  max resid 0.06874907 
## Run 15 stress 0.1682993 
## ... Procrustes: rmse 0.002937873  max resid 0.06479914 
## Run 16 stress 0.1682408 
## ... Procrustes: rmse 0.002518197  max resid 0.06480589 
## Run 17 stress 0.168084 
## ... Procrustes: rmse 0.002852725  max resid 0.0688647 
## Run 18 stress 0.1682252 
## ... Procrustes: rmse 0.002277517  max resid 0.06483624 
## Run 19 stress 0.1682913 
## ... Procrustes: rmse 0.003628881  max resid 0.06897773 
## Run 20 stress 0.168242 
## ... Procrustes: rmse 0.002564566  max resid 0.06479689 
## Run 21 stress 0.1680831 
## ... Procrustes: rmse 0.002833838  max resid 0.0687755 
## Run 22 stress 0.1682715 
## ... Procrustes: rmse 0.002732182  max resid 0.06484454 
## Run 23 stress 0.1682402 
## ... Procrustes: rmse 0.002551476  max resid 0.06478896 
## Run 24 stress 0.169357 
## Run 25 stress 0.1682819 
## ... Procrustes: rmse 0.003475259  max resid 0.06897655 
## Run 26 stress 0.1682244 
## ... Procrustes: rmse 0.002268476  max resid 0.06483125 
## Run 27 stress 0.1682643 
## ... Procrustes: rmse 0.003465414  max resid 0.06869292 
## Run 28 stress 0.1682656 
## ... Procrustes: rmse 0.003467675  max resid 0.06870807 
## Run 29 stress 0.168241 
## ... Procrustes: rmse 0.002545915  max resid 0.06480415 
## Run 30 stress 0.1680156 
## ... New best solution
## ... Procrustes: rmse 0.0001815101  max resid 0.003862929 
## ... Similar to previous best
## *** Solution reached
## 
## Call:
## metaMDS(comm = NMDSthree[, 6:144], k = 3, trymax = 1000) 
## 
## global Multidimensional Scaling using monoMDS
## 
## Data:     NMDSthree[, 6:144] 
## Distance: bray 
## 
## Dimensions: 3 
## Stress:     0.1680156 
## Stress type 1, weak ties
## Two convergent solutions found after 30 tries
## Scaling: centring, PC rotation, halfchange scaling 
## Species: expanded scores based on 'NMDSthree[, 6:144]'

Envfit results from Vegan package :

## 
## ***VECTORS
## 
##                     NMDS1    NMDS2     r2 Pr(>r)    
## JulianDate       -0.72223  0.69165 0.0743  0.660    
## Latitude          0.90919 -0.41638 0.2239  0.258    
## Longitude         0.89008  0.45580 0.2546  0.195    
## US_L3CODE         0.23608 -0.97173 0.3200  0.128    
## Order            -0.87248 -0.48865 0.7801  0.001 ***
## EDASOrder        -0.87248 -0.48865 0.7801  0.001 ***
## totalArea_sqMile -0.48524 -0.87438 0.4762  0.037 *  
## ELEVMEAN         -0.71649 -0.69759 0.5565  0.011 *  
## SLPMEAN          -0.24497 -0.96953 0.7939  0.001 ***
## wshdRain_mmyr    -0.46527 -0.88517 0.4796  0.036 *  
## siteRain_mmyr    -0.59859  0.80106 0.2534  0.208    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
## 
## ***FACTORS:
## 
## Centroids:
##                                                          NMDS1   NMDS2
## SeasonFall                                             -0.6971  0.5872
## SeasonOutside Sample Window                            -0.5772  0.1178
## SeasonSpring                                           -0.6572  0.2728
## GradientMACS                                           -0.6686  0.3964
## CoastalTRUE                                            -0.6686  0.3964
## US_L3NAMEMiddle Atlantic Coastal Plain                 -0.6506  0.6849
## US_L3NAMESoutheastern Plains                           -0.6785  0.2362
## US_L4NAMEChesapeake-Pamlico Lowlands and Tidal Marshes -0.6791  0.3657
## US_L4NAMEMid-Atlantic Flatwoods                        -0.6316  0.8978
## US_L4NAMERolling Coastal Plain                         -0.6785  0.2362
## ASSESS_REGPRO                                          -0.6786  0.2597
## ASSESS_REGTRO                                          -0.6316  0.8978
## TidalN                                                 -0.6668  0.4016
## TidalT                                                 -0.6791  0.3657
## VAHUSBCB                                               -0.6071  0.5407
## VAHUSBCU                                               -0.7208  0.5247
## VAHUSBYO                                               -0.6517  0.0599
## BasinChes. Bay and Small Coastal Basin                 -0.6071  0.5407
## BasinChowan and Dismal Swamp River Basin               -0.7208  0.5247
## BasinYork River Basin                                  -0.6517  0.0599
## Basin_CodeChowan-Dismal                                -0.7208  0.5247
## Basin_CodeSmall Coastal                                -0.6071  0.5407
## Basin_CodeYork                                         -0.6517  0.0599
## CountyCityNameCaroline                                 -0.7296 -0.0188
## CountyCityNameDinwiddie                                -0.8387  0.3481
## CountyCityNameHanover                                  -0.5737  0.1385
## CountyCityNameKing and Queen                           -0.5351  0.7157
## CountyCityNameNorthumberland                           -0.6791  0.3657
## CountyCityNameSouthampton                              -0.6316  0.8978
## CountyCityNameSussex                                   -0.7526 -0.2416
## WQS_CLASSIII                                           -0.7140  0.0904
## WQS_CLASSVII                                           -0.6433  0.5664
## WQS_SPSTDS                                             -0.6537  0.3536
## WQS_SPSTDSNEW-21                                       -0.8613  0.9534
## WQS_PWS                                                -0.6686  0.3964
## WQS_TROUT                                              -0.6686  0.3964
## WQS_TIER_III                                           -0.6686  0.3964
## 
## Goodness of fit:
##                    r2 Pr(>r)   
## Season         0.1838  0.384   
## Gradient       0.0000  1.000   
## Coastal        0.0000  1.000   
## US_L3NAME      0.2863  0.035 * 
## US_L4NAME      0.4372  0.032 * 
## ASSESS_REG     0.4251  0.006 **
## Tidal          0.0011  1.000   
## VAHUSB         0.2941  0.126   
## Basin          0.2941  0.126   
## Basin_Code     0.2941  0.126   
## CountyCityName 0.8722  0.002 **
## WQS_CLASS      0.3279  0.038 * 
## WQS_SPSTDS     0.1648  0.267   
## WQS_PWS        0.0000  1.000   
## WQS_TROUT      0.0000  1.000   
## WQS_TIER_III   0.0000  1.000   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
## 
## 840 observations deleted due to missingness

Plot with Station IDs

Plot with Axis 3

Plot with Species

Season

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$Season,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Fall  Outside Sample Window Spring
## delta 0.673 0.6843                0.677 
## n     414   13                    427   
## 
## Chance corrected within-group agreement A: 0.03403 
## Based on observed delta 0.6752 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Season with continuous variable vectors

Ecoregion

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$US_L3NAME,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Blue Ridge Central Appalachians Middle Atlantic Coastal Plain
## delta 0.6029     0.612                0.5932                       
## n     154        40                   25                           
##       Northern Piedmont Piedmont Ridge and Valley Southeastern Plains
## delta 0.6522            0.6224   0.6621           0.6438             
## n     101               138      259              137                
## 
## Chance corrected within-group agreement A: 0.08929 
## Based on observed delta 0.6365 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Basin

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$Basin_Code,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Appomattox Chowan-Dismal James-Lower James-Middle James-Upper New   
## delta 0.5752     0.6644        0.6262      0.6185       0.6573      0.6587
## n     15         33            36          61           120         78    
##       Potomac-Lower Potomac-Shenandoah Rappahannock Roanoke Small Coastal
## delta 0.6925        0.6606             0.674        0.6185  0.5796       
## n     31            42                 144          87      21           
##       Tennessee-Big Sandy Tennessee-Clinch Tennessee-Holston Yadkin York  
## delta 0.6108              0.6339           0.632             0.5781 0.6727
## n     16                  50               53                4      63    
## 
## Chance corrected within-group agreement A: 0.07359 
## Based on observed delta 0.6475 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Admin Region

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$ASSESS_REG,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       BRRO   NRO    PRO    SWRO   TRO    VRO   
## delta 0.6493 0.6978 0.6435 0.6405 0.5852 0.6483
## n     250    195    122    156    21     110   
## 
## Chance corrected within-group agreement A: 0.06113 
## Based on observed delta 0.6562 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Sample Method

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$Gradient,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       MACS   Riffle
## delta 0.6505 0.6619
## n     163    691   
## 
## Chance corrected within-group agreement A: 0.05608 
## Based on observed delta 0.6598 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

BioRegion- Not in dataset

Stream Order

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$Order,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       1      2      3     4      5      6     
## delta 0.6754 0.6904 0.665 0.6638 0.6289 0.4322
## n     277    248    172   114    41     2     
## 
## Chance corrected within-group agreement A: 0.03666 
## Based on observed delta 0.6733 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Water Quality Standard Class

## 
## Call:
## mrpp(dat = bugsnms[, 6:144], grouping = samplescoresenv$WQS_CLASS,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       III   IV     V      VI     VII   
## delta 0.697 0.6508 0.6376 0.6115 0.6389
## n     331   185    87     209    42    
## 
## Chance corrected within-group agreement A: 0.05979 
## Based on observed delta 0.6572 and expected delta 0.6989 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Natural Trout Water WQS?